This section is intended to provide a background to the various embodiments of the technology described in this disclosure. The description in this section may include concepts that could be pursued, but are not necessarily ones that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, what is described in this section is not prior art to the description and/or claims of this disclosure and is not admitted to be prior art by the mere inclusion in this section.
To combat the frequency selective fading phenomenon which is common in mobile communications, a so called frequency selective scheduling (FSS) technique is widely used in mobile communication systems including recent LTE systems. The fundament principle of the FSS technique is to selectively use radio resource units (e.g., RBs in LTE systems) associated with non-faded or less-faded frequencies for data transmission, so that the data transmission is carried out using only radio resource units of high quality and is thus significantly improved in both reliability and efficiency.
The FSS technique can be applied for both downlink (DL) and uplink (UL) transmissions in LTE systems, but is subject to different constraints and accordingly aims at different targets.
Specifically, in the downlink direction, as an eNB typically has inexhaustible power supply and adequate processing power, distributed RBs can be allocated for downlink transmission. Thus, with respect to the DL FSS, it is always preferable for the eNB to preferentially select RBs, individually having the best qualities, for downlink transmission to a User Equipment (UE), regardless of the frequencies that the RBs are associated with (namely, the positions of the RBs in the frequency dimension). In this way, all data stored in the transmission buffer of the eNB can be transmitted to the UE using the minimum amount of RBs in a buffer limited case (to be set forth in additional detail hereinbelow), or the most data stored in the transmission buffer can be transmitted to the UE in an RB limited case (to be set forth in additional detail hereinbelow).
On the other hand, in the uplink direction, as a UE is typically limited in power supply and processing power, RBs must be allocated consecutively for uplink transmission to reduce Peak to Average Power Ratio (PAPR) and hence to reduce power consumption of the UE. Under such a constraint, with respect to the UL FSS, it is preferable for the eNB to select a group of consecutive RBs, collectively having the best quality, for uplink transmission from the UE. In this way, all data stored in the transmission buffer of the UE can be transmitted to the eNB using the minimum amount of consecutive RBs in the buffer limited case, or the most data stored in the transmission buffer can be transmitted to the eNB in the RB limited case.
The quality of an RB can be measured in terms of Signal to Interference plus Noise Ratio (SINR), Signal to Noise Ratio (SNR), number of Effective Raw Bits (ERBs), or any other index which may quantify the quality of a RB. As used herein, the term “ERB” refers to raw bits that can be decoded correctly from an RB and, in other words, effectively conveyed by the RB.
Using the number of ERBs to assess the quality of RB, the target for UL FSS can be reworded as selecting a group of consecutive RBs, having the largest total number of ERBs, for uplink transmission from the UE.
To this end, it is necessary to jointly select the number of RBs constituting the group of consecutive RBs and the positions of the consecutive RBs. Although many prior art technical solutions have been proposed for UL FSS, none of them makes such a joint selection.
Instead, according to a first typical solution (hereinafter denoted as solution 1) known as peak RB expansion, one RB of the best quality is initially selected and then RBs adjoining the selected RB are selected iteratively until a group of consecutive RBs sufficient to empty the transmission buffer is formed or there is no more RB available.
According to a second typical solution (hereinafter denoted as solution 2), the size of the group is initially decided for example through theoretical calculation, model simulation or experientially, and then the entire set of available RBs is searched through using a sliding window, whose size is equal to the decided group size, to find a group of consecutive RBs having the largest total number of ERBs or just sufficient to empty the transmission buffer.
FIG. 1 gives an example of the groups of consecutive RBs selected according to both the above solutions. As illustrated, the group of RBs 19-23 selected by using solution 1 contains the 22nd RB, which has the largest number of ERBs. However, this group of RBs as a whole does not have the largest total number of ERBs. The group of RBs 3-7 selected by using solution 2 contains the largest total number of ERBs for a window size of 5 RBs. However, the transmission buffer may accommodate only an amount of data which can be carried just by RBs 4-7. Thus, without jointly selecting size and position of the group of consecutive RBs, neither solution 1 or 2 provides the optimal result for UL FSS (i.e., the minimum amount of consecutive RBs sufficient to empty the transmission buffer).
In other aspects, none of the existing solutions for UL FSS takes into account fragmentation of an available frequency band. However, even when the 1st UE is scheduled, the frequency band may already be split into several fragments. Without considering this, solution 1 may choose a non-optimal fragment containing the RB having largest number of ERBs, whereas solution 2 may decide a group size larger than any fragment.
Additionally, all existing solutions for UL FSS assume a buffer size limited case where the transmission buffer can be emptied by available RBs. In this case, the optimal goal of UL FSS is to select the minimum amount of consecutive RBs from the available RBs for empting the transmission buffer. However, in practical scenarios, a RB limited case where the transmission buffer cannot be emptied by available RBs is also very common. In this case, the optimal goal of UL FSS is to select all RBs on the fragment which can carry the largest amount of ERBs. Without distinguishing the RB limited case from the buffer size limited case and adaptively changing the optimal goal of UL FSS, it is impossible to flexibly reduce the complexity of making the joint selection, and the optimal result for the PB limited case may not be obtained.